Job Description
Job Description
Founding Senior Backend Engineer (Data Platform / Integrations)
Location: New York City — In-Person
The Opportunity
Our client is hiring a Founding Senior Backend Engineer to own the data platform end-to-end and build the team around it. This is a true founding role: you will define canonical data models, ship the event backbone, enable analytics/experimentation, and create the integration architecture that makes adding EMR #5 configuration—not months of bespoke engineering.
If you're energized by unglamorous but high-leverage infrastructure (data modeling, pipelines, events, integrations), this is a rare seat.
What You'll Own
1) Outcome Data Layer (Instrumentation + Measurement)
Build the instrumentation layer that ties every agent decision to customer-level business metrics—e.g., client retention, caregiver satisfaction, authorization utilization, hours erosion. This becomes the foundation for experimentation, ROI claims, ML improvements, and product strategy.
2) Real-Time Event Backbone
Design an event-driven architecture where visit status changes, clock-ins, call-outs, ranking decisions, and workflow outcomes flow in real time—so internal systems (and future products) can consume events without constant EMR polling or rate-limit band-aids.
3) Integration Platform + Canonical Models
Create canonical data models across WellSky, HHAeXchange, AlayaCare, and Axxess so adding the next EMR is configuration-driven. This also unlocks revenue-cycle automation by enabling unified authorization and billing models.
4) Analytics & Experimentation Tooling
Build the warehouse + tooling so engineers can answer: “Did this change improve customer outcomes?” quickly and consistently—without writing one-off queries every time.
What Our Client Is Looking For
You're likely a fit if you are:
- Systems-minded and data-opinionated: you treat data modeling as a craft and can explain why entities should relate a certain way
- Comfortable with messy reality: you're excited by pipelines, joins, ETL/ELT, and cleaning inconsistent third-party data
- Event-driven by default: you've built (or deeply understand) real-time architectures, streaming/event backbones, and durable systems
- Integration-savvy: you've shipped platforms that unify multiple external systems into clean internal abstractions
- AI-native and curious: you naturally look for leverage (LLMs for parsing/structuring, automation for data QA, agent-based extraction when APIs don't exist)
Bonus signals
- Experience with healthcare workflows, EMRs/EHRs, home health, or revenue-cycle concepts (authorization, billing, reimbursement)
- Familiarity with healthcare data modeling standards (e.g., FHIR-style entity thinking)
- Experience building experimentation frameworks or measurement systems tied to business outcomes
- Background in data platform teams (data engineering + backend/platform) at high-growth startups
What Success Looks Like (The Arc)
Q2: Ship the outcome data layer + real-time event backbone. Make experimentation and measurable ROI a default.
Q3: Deliver the integration abstraction + canonical models. EMR #5 becomes configuration. RCM roadmap becomes real.
Year-end: You've built and are leading a 3–5 person data platform team (integration, data engineering, analytics). You're operating as the Head of Data Platform.
Why This Role
- Founding-level ownership on a platform that directly drives revenue outcomes
- Complex, high-impact systems work: data, events, integrations, measurement, experimentation
- Clear path to technical leadership and building a team
- Real customers, real workflows, and real-world leverage—your architecture decisions compound fast